from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting("sklearnex", config="config.yml")
reporting.make_report()
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.010 | 0.0 | NaN | 7.720 | 0.0 | -1 | 1 | NaN | 0.048 | 0.005 | 0.215 | 0.217 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.213 | 0.0 | -1 | 5 | NaN | 0.046 | 0.001 | 0.240 | 0.240 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.484 | 0.0 | 1 | 100 | NaN | 0.045 | 0.001 | 0.237 | 0.237 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.137 | 0.0 | -1 | 100 | NaN | 0.046 | 0.001 | 0.245 | 0.245 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.613 | 0.0 | 1 | 5 | NaN | 0.045 | 0.001 | 0.232 | 0.232 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | NaN | 7.471 | 0.0 | 1 | 1 | NaN | 0.046 | 0.001 | 0.233 | 0.233 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.364 | 0.0 | -1 | 1 | NaN | 0.009 | 0.001 | 0.514 | 0.515 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.360 | 0.0 | -1 | 5 | NaN | 0.009 | 0.001 | 0.518 | 0.519 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.377 | 0.0 | 1 | 100 | NaN | 0.009 | 0.000 | 0.472 | 0.472 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.372 | 0.0 | -1 | 100 | NaN | 0.009 | 0.000 | 0.476 | 0.476 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | NaN | 0.350 | 0.0 | 1 | 5 | NaN | 0.009 | 0.000 | 0.498 | 0.499 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | NaN | 0.388 | 0.0 | 1 | 1 | NaN | 0.008 | 0.000 | 0.517 | 0.517 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.865 | 0.128 | NaN | 0.000 | 0.002 | -1 | 1 | 0.663 | 0.194 | 0.016 | 9.629 | 9.661 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.003 | NaN | 0.000 | 0.021 | -1 | 1 | 1.000 | 0.008 | 0.000 | 2.678 | 2.678 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.624 | 0.043 | NaN | 0.000 | 0.003 | -1 | 5 | 0.757 | 0.191 | 0.003 | 13.732 | 13.734 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | NaN | 0.000 | 0.023 | -1 | 5 | 1.000 | 0.008 | 0.000 | 2.949 | 2.950 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.016 | 0.060 | NaN | 0.000 | 0.002 | 1 | 100 | 0.882 | 0.224 | 0.005 | 8.999 | 9.002 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.001 | NaN | 0.000 | 0.020 | 1 | 100 | 1.000 | 0.008 | 0.000 | 2.513 | 2.515 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.633 | 0.060 | NaN | 0.000 | 0.003 | -1 | 100 | 0.882 | 0.223 | 0.005 | 11.814 | 11.816 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.004 | NaN | 0.000 | 0.025 | -1 | 100 | 1.000 | 0.008 | 0.001 | 3.092 | 3.114 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.988 | 0.035 | NaN | 0.000 | 0.002 | 1 | 5 | 0.757 | 0.184 | 0.005 | 10.804 | 10.809 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.001 | NaN | 0.000 | 0.019 | 1 | 5 | 1.000 | 0.008 | 0.000 | 2.452 | 2.453 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.091 | 0.010 | NaN | 0.001 | 0.001 | 1 | 1 | 0.663 | 0.182 | 0.005 | 6.000 | 6.003 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.003 | NaN | 0.000 | 0.020 | 1 | 1 | 1.000 | 0.007 | 0.000 | 2.780 | 2.781 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.642 | 0.019 | NaN | 0.000 | 0.002 | -1 | 1 | 0.896 | 0.027 | 0.001 | 60.056 | 60.105 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.002 | NaN | 0.000 | 0.004 | -1 | 1 | 1.000 | 0.001 | 0.000 | 6.258 | 6.299 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.482 | 0.020 | NaN | 0.000 | 0.002 | -1 | 5 | 0.922 | 0.029 | 0.002 | 86.413 | 86.554 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.005 | 0.002 | NaN | 0.000 | 0.005 | -1 | 5 | 1.000 | 0.001 | 0.000 | 7.722 | 7.757 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.905 | 0.054 | NaN | 0.000 | 0.002 | 1 | 100 | 0.929 | 0.064 | 0.004 | 29.535 | 29.593 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 3.784 | 3.818 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.556 | 0.034 | NaN | 0.000 | 0.003 | -1 | 100 | 0.929 | 0.066 | 0.002 | 38.570 | 38.580 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.003 | NaN | 0.000 | 0.006 | -1 | 100 | 1.000 | 0.001 | 0.000 | 7.436 | 7.459 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.899 | 0.022 | NaN | 0.000 | 0.002 | 1 | 5 | 0.922 | 0.027 | 0.001 | 69.820 | 69.845 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | 1 | 5 | 1.000 | 0.001 | 0.000 | 4.520 | 4.562 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.018 | 0.007 | NaN | 0.000 | 0.001 | 1 | 1 | 0.896 | 0.026 | 0.002 | 38.449 | 38.523 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.001 | 0.000 | 2.951 | 3.000 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.625 | 0.025 | NaN | 0.030 | 0.0 | -1 | 1 | NaN | 0.861 | 0.346 | 3.050 | 3.287 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.307 | 0.065 | NaN | 0.024 | 0.0 | -1 | 5 | NaN | 0.699 | 0.040 | 4.729 | 4.736 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.250 | 0.049 | NaN | 0.025 | 0.0 | 1 | 100 | NaN | 0.737 | 0.015 | 4.413 | 4.414 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.236 | 0.076 | NaN | 0.025 | 0.0 | -1 | 100 | NaN | 0.667 | 0.010 | 4.851 | 4.851 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.251 | 0.062 | NaN | 0.025 | 0.0 | 1 | 5 | NaN | 0.733 | 0.016 | 4.432 | 4.433 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.241 | 0.049 | NaN | 0.025 | 0.0 | 1 | 1 | NaN | 0.678 | 0.014 | 4.784 | 4.785 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.017 | 0.0 | -1 | 1 | NaN | 0.004 | 0.002 | 0.239 | 0.280 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.031 | 0.0 | -1 | 5 | NaN | 0.002 | 0.002 | 0.242 | 0.310 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.000 | 0.000 | NaN | 0.035 | 0.0 | 1 | 100 | NaN | 0.001 | 0.001 | 0.445 | 0.604 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.029 | 0.0 | -1 | 100 | NaN | 0.001 | 0.000 | 0.552 | 0.558 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.000 | 0.000 | NaN | 0.032 | 0.0 | 1 | 5 | NaN | 0.001 | 0.000 | 0.566 | 0.567 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.000 | 0.000 | NaN | 0.035 | 0.0 | 1 | 1 | NaN | 0.001 | 0.000 | 0.579 | 0.582 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.804 | 0.997 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.102 | 0.004 | 7.893 | 7.899 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.000 | 0.000 | 10.033 | 10.382 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.938 | 0.337 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.175 | 0.003 | 5.350 | 5.351 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 0.000 | 0.000 | 7.537 | 7.782 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 4.839 | 0.414 | NaN | 0.000 | 0.005 | 1 | 100 | 0.951 | 0.536 | 0.011 | 9.020 | 9.022 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 0.001 | 0.000 | 4.063 | 4.186 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.917 | 0.281 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.526 | 0.016 | 5.546 | 5.549 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | NaN | 0.000 | 0.005 | -1 | 100 | 1.000 | 0.001 | 0.000 | 6.651 | 6.872 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.555 | 0.363 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.183 | 0.004 | 8.484 | 8.486 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 5 | 1.000 | 0.000 | 0.000 | 3.854 | 3.975 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.840 | 0.304 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.096 | 0.002 | 8.762 | 8.763 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 4.047 | 4.252 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.020 | NaN | 0.001 | 0.000 | -1 | 1 | 0.891 | 0.000 | 0.000 | 72.439 | 74.303 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | NaN | 0.000 | 0.002 | -1 | 1 | 1.000 | 0.000 | 0.000 | 30.269 | 31.194 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.002 | NaN | 0.001 | 0.000 | -1 | 5 | 0.911 | 0.001 | 0.000 | 33.631 | 34.207 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.000 | 0.000 | 27.814 | 28.676 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.034 | 0.011 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.004 | 0.000 | 7.692 | 7.730 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.000 | 0.000 | 6.567 | 6.831 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.005 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.005 | 0.001 | 7.512 | 7.742 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | NaN | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.000 | 0.000 | 23.804 | 24.293 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.020 | 0.002 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.001 | 0.000 | 30.763 | 30.869 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.000 | 0.000 | NaN | 0.000 | 0.000 | 1 | 5 | 1.000 | 0.000 | 0.000 | 5.066 | 5.353 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.017 | 0.001 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.000 | 0.000 | 42.908 | 43.165 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.000 | 0.000 | 8.085 | 8.329 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.500 | 0.066 | 30 | 0.032 | 0.0 | random | NaN | 0.405 | 0.033 | 1.235 | 1.239 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.558 | 0.014 | 30 | 0.029 | 0.0 | k-means++ | NaN | 0.421 | 0.034 | 1.325 | 1.329 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.312 | 0.259 | 30 | 0.151 | 0.0 | random | NaN | 2.590 | 0.070 | 2.051 | 2.052 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.503 | 0.028 | 30 | 0.145 | 0.0 | k-means++ | NaN | 2.669 | 0.049 | 2.062 | 2.062 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.009 | 0.000 | random | 0.001 | 0.0 | 0.0 | 9.120 | 12.723 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 1.000 | 0.0 | 0.0 | 8.726 | 13.163 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.001 | 0.000 | 30 | 0.011 | 0.000 | k-means++ | 0.001 | 0.0 | 0.0 | 10.285 | 11.411 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.001 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 17.615 | 18.591 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.412 | 0.000 | random | 0.002 | 0.0 | 0.0 | 7.422 | 7.926 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | random | 1.000 | 0.0 | 0.0 | 13.750 | 14.196 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.437 | 0.000 | k-means++ | 0.002 | 0.0 | 0.0 | 6.811 | 7.174 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | k-means++ | 1.000 | 0.0 | 0.0 | 14.222 | 14.879 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.074 | 0.003 | 20 | 0.002 | 0.0 | random | NaN | 0.026 | 0.003 | 2.862 | 2.877 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.211 | 0.006 | 20 | 0.001 | 0.0 | k-means++ | NaN | 0.081 | 0.003 | 2.602 | 2.604 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.201 | 0.006 | 20 | 0.040 | 0.0 | random | NaN | 0.113 | 0.013 | 1.778 | 1.789 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.576 | 0.011 | 20 | 0.014 | 0.0 | k-means++ | NaN | 0.310 | 0.007 | 1.858 | 1.858 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | adjusted_rand_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | random | 0.000 | 0.000 | 0.0 | 4.843 | 4.865 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 1.000 | 0.000 | 0.0 | 11.740 | 11.994 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | k-means++ | 0.001 | 0.000 | 0.0 | 3.727 | 3.746 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 1.000 | 0.000 | 0.0 | 11.093 | 11.423 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.360 | 0.000 | random | 0.279 | 0.001 | 0.0 | 2.015 | 2.018 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.001 | 0.002 | random | 1.000 | 0.000 | 0.0 | 10.626 | 11.009 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.301 | 0.000 | k-means++ | 0.317 | 0.001 | 0.0 | 2.911 | 2.950 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.001 | 0.002 | k-means++ | 1.000 | 0.000 | 0.0 | 11.446 | 11.532 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 10.396 | 0.457 | [20] | 0.077 | 0.000 | NaN | NaN | NaN | NaN | NaN | 1.738 | 0.021 | 5.981 | 5.981 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.857 | 0.573 | [26] | 0.093 | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.719 | 0.030 | 1.191 | 1.192 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 1.795 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.595 | 1.285 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.014 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 0.334 | 0.340 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 5.012 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.005 | 0.001 | 0.348 | 0.365 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 1.202 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.001 | 0.000 | 0.109 | 0.109 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.169 | 0.004 | NaN | 0.473 | 0.0 | NaN | NaN | NaN | 0.176 | 0.004 | 0.959 | 0.959 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.098 | 0.082 | NaN | 0.728 | 0.0 | NaN | NaN | NaN | 0.301 | 0.251 | 3.644 | 4.742 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.0 | NaN | 8.338 | 0.0 | NaN | NaN | 0.083 | 0.017 | 0.003 | 0.570 | 0.579 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.0 | NaN | 1.526 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.487 | 0.522 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.0 | NaN | 6.506 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.000 | 0.384 | 0.565 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.0 | NaN | 0.017 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.582 | 0.611 | See | See |